• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.161-161
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• 2019

Water security issues, stimulated by increasing population and changing climate, are growing and pausing major challenges for water resources managers around the world. Proper utilization, management and distribution of all available water resources is key to sustainable development for achieving water security To alleviate the water shortage, most of the current research on multi-sources combined water supplies depends on an overall generalization of regional water supply systems, which are seldom broken down into the detail required to address specific research objectives. This paper proposes the concept of optimization framework on multi water sources selection. A multi-objective water allocation model with four objective functions is introduced in this paper. Harmony search algorithm is employed to solve the applied model. The objective functions addresses the economic, environmental, and social factors that must be considered for achieving a sustainable water allocation to solve the issue of water security.

• Journal of Ecology and Environment
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• v.40 no.1
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• pp.34-44
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• 2016

Background: Little is known about how chemical water quality is associated with ecological stream health in relation to landuse patterns in a watershed. We evaluated spatial characteristics of water quality characteristics and the ecological health of Dongjin-River basin, Korea in relation to regional landuse pattern. The ecological health was assessed by the multi-metric model of Index of Biological Integrity (IBI), and the water chemistry data were compared with values obtained from the health model. Results: Nutrient and organic matter pollution in Dongjin-River basin, Korea was influenced by land use pattern and the major point sources, so nutrients of TN and TP increased abruptly in Site 4 (Jeongeup Stream), which is directly influenced by wastewater treatment plants along with values of electric conductivity (EC), bacterial number, and sestonic chlorophyll-a. Similar results are shown in the downstream (S7) of Dongjin River. The degradation of chemical water quality in the downstream resulted in greater impairment of the ecological health, and these were also closely associated with the landuse pattern. Forest region had low nutrients (N, P), organic matter, and ionic content (as the EC), whereas urban and agricultural regions had opposite in the parameters. Linear regression analysis of the landuse (arable land; $A_L$) on chemicals indicated that values of $A_L$ had positive linear relations with TP ($R^2=0.643$, p < 0.01), TN ($R^2=0.502$, p < 0.05), BOD ($R^2=0.739$, p < 0.01), and suspended solids (SS; ($R^2=0.866$, p < 0.01), and a negative relation with TDN:TDP ratios ($R^2=0.719$, p < 0.01). Conclusions: Chemical factors were closely associated with land use pattern in the watershed, and these factors influenced the ecological health, based on the multimetric fish IBI model. Overall, the impairments of water chemistry and the ecological health in Dongjin-River basin were mainly attributes to point-sources and land-use patterns.

• Journal of the Korean Society of Systems Engineering
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• v.12 no.1
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• pp.73-87
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• 2016

Combining power generation and water production by desalination is economically advantageous. Most desalination projects use fossil fuels as an energy source, and thus contribute to increased levels of greenhouse gases. Environmental concerns have spurred researchers to find new sources of energy for desalination plants. The coupling of nuclear power production with desalination is one of the best options to achieve growth with lower environmental impact. In this paper, we will per-form a sensitivity study of coupling nuclear power to various combinations of desalination technology: {1} thermal (MSF [Multi-Stage Flashing], MED [Multi-Effect Distillation], and MED-TVC [Multi-Effect Distillation with Thermal Vapour Compression]); {2} membrane RO [Reverse Osmosis]; and {3} hybrid (MSF-RO [Multi-Stage Flashing & Reverse Osmosis] and MED-RO [Multi-Effect Distillation & Reverse Osmosis]). The Korean designed reactor plant, the APR1400 will be modeled as the energy production facility. The economical evaluation will then be executed using the computer program DEEP (Desalination Economic Evaluation Program) as developed by the IAEA. The program has capabilities to model several types of nuclear and fossil power plants, nuclear and fossil heat sources, and thermal distillation and membrane desalination technologies. The output of DEEP includes levelized water and power costs, breakdowns of cost components, energy consumption, and net saleable power for any selected option. In this study, we will examine the APR1400 coupled with a desalination power plant in the Kingdom of Saudi Arabia (KSA) as a prototypical example. The KSA currently has approximately 20% of the installed worldwide capacity for seawater desalination. Utilities such as power and water are constructed and run by the government. Per state practice, economic evaluation for these utilities do not consider or apply interest or carrying cost. Therefore, in this paper the evaluation results will be based on two scenarios. The first one assumes the water utility is under direct government control and in this case the interest and discount rate will be set to zero. The second scenario will assume that the water utility is controlled by a private enterprise and in this case we will consider different values of interest and discount rates (4%, 8%, & 12%).

• KCID journal
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• v.21 no.1
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• pp.127-140
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• 2014

Recently drastic climate changes(e.g., extreme floods and droughts) are often taking place around the world. Even an increase in uncertainty, population, and mega cities has caused drastic changes in water recycle process. As in other countries, Korea has faced some issues relevant to water security. In response to these changes, Smart Water Grid(SWG) system combining the current water resources management with ICT (Information and Communications Technology) is considered as a new paradigm for the Korean water resources management. This study aims to explore and identify influential factors contributing to the SWG system's application to analyze the importance and role of those factors, and then to offer a policy suggestion for the successful application of the SWG system along with legislative improvements in Korea. In this study, we looked at different barriers related to the SWG application and also the complicated Korean water laws, enacted by different ministries and in order to efficiently apply the SWG system to the current Korean water resources management structures. This study employed qualitative research methods to analyze and identify the priorities of the tasks to be implemented by analyzing conditions for the SWG application, especially related to multi water sources and micro water grid, because legal and institutional measures can be more important to manage conflicts between different stakeholders once the SWG enters a phase of standardization and commercialization from its development stage.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.1052-1065
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• 2024

Advanced Pressurized Water Reactors (APWRs) and Boiling Water Reactors (BWRs) employ a suppression pool as a heat sink to prevent containment overpressure. Steam can be discharged into the pool through multi-hole spargers or blowdown pipes in both normal and accident conditions. Direct Contact Condensation (DCC) creates sources of momentum and heat. The competition between these two sources determines the development of thermal stratification or mixing of the pool. Thermal stratification is of safety concern as it reduces the cooling capability compared to a completely mixed pool condition. In this work we develop a scaling approach to prediction of the thermal stratification in a water pool induced by steam injection through spargers. Experimental data obtained from large-scale pool tests conducted in the PPOOLEX and PANDA facilities, as well as simulation results obtained using validated codes are used to develop the scaling. Two injection orientations, namely radial injection through multi-hole Sparger Head (SH) and vertical injection through Load Reduction Ring (LRR), are considered. We show that the erosion rate of the cold layer can be estimated using the Richardson number. In this work, scaling laws are proposed to estimate both the (i) transient erosion velocity and (ii) the stable position of the thermocline. These scaling laws are then implemented into a 1D model to simulate the thermal behavior of the pool during steam injection through the sparger.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.2
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• pp.57-62
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• 2017

The heat transfer performance of a multi-heat-source fluidized bed heat exchanger was analyzed. The fluidized bed heat exchanger examined in this study can simultaneously recover the waste heat from gas, water vapor, and hot water. The effects of waste water flow rate, gas flow rate, and cooling water flow rate were examined to find their experimental correlations with the heat transfer coefficient. A computer program using the correlations was developed in this study to predict the thermal performance of the fluidized bed heat exchanger. The calculated heat transfer rates of gas, water vapor, waste water, and cooling water were compared with the measured values. It was found that the error of the calculated values was less than 12%.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.59-70
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• 2022

Water distribution systems (WDSs) are a representative infrastructure injecting chlorine to disinfect the pathogenic microorganisms and supplying water from sources to consumers. Also, WDSs prescribe to maintain the usual standard (0.1-4.0 mg/L) of residual chlorine. However, the user's usage pattern, water age, network shape, and type affect the hydraulic features (i.e. nodal pressure, pipe velocity) and water quality features (i.e., the residual chlorine concentration). Therefore, this study developed an optimization approach for optimizing WDSs considering water quality-hydraulic factors using Multi-objective Harmony Search (MOHS). The design cost and the system resilience were applied as the design objective functions, and the nodal pressure and the concentration of residual chlorine are used as constraints. The derived optimal designs through this approach were analyzed according to network characteristics such as the network shapes and type. These optimal designs can meet the safety of economic and water quality aspects to increase user acceptance.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.4
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• pp.511-517
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• 2011

To evaluate carbon emission in water treatment processes, LCA (life cycle assessment) was applied to 8 multi-regional water treatment plants (WTPs) from intake to supply of tap water. Investigation of 8 WTPs revealed that average carbon emission for 1 $m^3$ of tap water was 221 g. Major carbon emission sources in water supply system were intake and supply processes. Meanwhile, mixing process was the main carbon emission source in unit water treatment processes. Carbon emission was proportional to the turbidity and COD of raw water. Intake of better raw water and minimization of energy consumption in unit processes are needed to reduce carbon emission in the WTPs. In addition, comparison of carbon emission among WTPs can be used as a parameter for optimization of operation and maintenance of water treatment processes.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.109.2-109.2
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• 2011

We have carried out a multi-epoch, simultaneous 22GHz $H_2O$ and 44GHz class I $CH_3OH$ maser survey of 109 low-mass protostars. $H_2O$ maser emission was detected in 23 sources, while $CH_3OH$ maser emission in 12 sources. Eight of the $CH_3OH$ detected sources are new detections. For comparison, only four low-mass protostars have been previously found to emit the maser emisison. We investigate difference between the properties of the two masers, such as relative velocity with respect to molecular gas and variability. We also compare the isotropic luminosities of both masers with the bolometric luminosity of the central star.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.